Knowledge based optimization
Keywords:
complex systems, multi-objective optimization, fuzzy logic, modal logic, multi-valued logicAbstract
Optimization theory has advanced considerably during the last three decades, as illustrated by a vast number of published books, surveys, and papers concerning this subject. However, for optimization of complex systems that may not be modeled exactly by Ludwig von Bertalanffy's general system theory, we may need a new philosophy based on rather non-conventional logics. It is represented bellow.
References
[1] J .F. Baldwin. A new approach to approximate reasoning using fuzzy logic, fuzzy set and system. Nor. Holland pub. comp., 1979.
[2] A. E. Bellman, L. A. Zadeh. Decision-making in a fuzzy environment. Man. Sc., 141- 164, 1970.
[3] Chr. Boller. State of the art. And trends in using smart materials and systems in transportation vehicles. Proc. Instn. Mech. Engrs., 212, 1, 149- 158, 1997.
[4] G. Boolos. The logic of provability. Cambridge Uni. Press., 1993.
[5] T. Chi. A theory of geotechnical uncertainty. Tech. University of Gdańsk, Poland 2000.
[2] A. E. Bellman, L. A. Zadeh. Decision-making in a fuzzy environment. Man. Sc., 141- 164, 1970.
[3] Chr. Boller. State of the art. And trends in using smart materials and systems in transportation vehicles. Proc. Instn. Mech. Engrs., 212, 1, 149- 158, 1997.
[4] G. Boolos. The logic of provability. Cambridge Uni. Press., 1993.
[5] T. Chi. A theory of geotechnical uncertainty. Tech. University of Gdańsk, Poland 2000.
Published
2023-01-18
Issue
pp. 283-291
Section
Articles
License
Copyright © The Author(s).
This work is licensed under the Creative Commons Attribution 4.0 International CC BY 4.0.
How to Cite
Tran, C. (2023). Knowledge based optimization. Computer Assisted Methods in Engineering and Science, 11(4), 283-291. https://cames3.ippt.pan.pl/index.php/cames/article/view/1026
